Zurich, Switzerland | LinkedIn | GitHub | 📧 [email protected]

Data & AI Engineer with 7+ years of experience designing scalable cloud data platforms and applied machine learning solutions.
Proven track record of delivering business value through large-scale data migrations, recommender systems reaching millions of users, and applied agentic AI workflows.
Passionate about bridging technical expertise and business needs through consulting, architecture design, and training — with recent focus on MLOps, LLMs, and enterprise-scale AI integration.

• Data Engineering & Cloud: Apache Spark, Kafka, NiFi, Flink | AWS (Redshift, Glue) | GCP (BigQuery, Dataproc) | Azure (Fabric, Synapse) | Cloudera
• DevOps & MLOps: Terraform, Airflow, Azure DevOps, GitHub Actions, MLflow
• Machine Learning & AI: PyTorch, scikit-learn, TensorFlow | Recommender Systems, Computer Vision, NLP
• Agentic AI & LLMs: OpenAI SDK, CrewAI, Hugging Face Transformers | RAG, PEFT

Senior Solutions Engineer — Cloudera (09/2022 – Present)

• Trained 50+ data scientists at a national bank on MLflow & MLOps; authored reusable workshop materials now used across EMEA.
• Delivered “Agentic AI 101” workshops for Solutions Engineers, driving adoption of next-gen AI workflows.
• Led an OCR POC with Qwen + PEFT, integrating domain knowledge into an agentic workflow and outperforming the customer’s baseline.
• Scaled a central bank’s migration to AWS on CDP, growing into one of Cloudera’s largest cloud customers worldwide.
• Maintainer of Cloudera Data Engineering Hands-on Labs used across EMEA workshops

Senior Data Engineer — ING (03/2021 – 08/2022)

• Optimized Spark pipelines and migrated to streaming, powering a recommender system for millions of customers.
• Improved CI/CD for experimentation & A/B testing, increasing CTR relevance by 50%.

Data Scientist — Lufthansa Industry Solutions (2019 – 2021)

• Helped clients identify and realize business value through applied Data Science & Engineering.

Data Scientist — Brose (2018 – 2019)

• Built computer vision solutions for semiconductor manufacturing quality inspection.
• 📺 Demo Video

• 📚 MLOps & MLflow Workshop Materials — Hands-on labs for training data scientists in MLOps with MLflow and Cloudera AI.
• 📺 Brose Computer Vision Demo — Deep learning CV for manufacturing QA.

• M.Sc. Mechanical Engineering — FAU Erlangen-Nürnberg (2018)
• B.Sc. International Production Engineering & Management — FAU Erlangen-Nürnberg (2015)

• Cloudera Machine Learning Engineer | Cloudera Data Engineer
• AWS Solutions Architect Associate (ongoing)
• Udacity Data Engineering Nanodegree
• Spark & Big Data (Udemy), Bayesian Statistics (Coursera)